Senior Product Builder

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.

We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

As a Senior Product Builder at EarnIn, you’ll help bring our mission to life. EarnIn is making AI-native work a core capability. It’s how we design, build, and ship. The products you own will run in production, making real decisions for real people who depend on EarnIn to access their pay when it matters most. You’ll bring a strong technical foundation to product work: setting product strategy, uncovering new insights, and driving execution on new, zero-to-one initiatives. You’ll partner with engineers, designers, and domain leads, and build the depth to lead new product bets as they come up.

This is a hybrid position in our Mountain View HQ that requires in-office work 2 days a week. The Mountain View base salary range for this full-time position is $229,661 to $280,697, plus equity and benefits. Our salary ranges are determined by role, level, and location. 

• →Own technical product strategy. Define what we build and why, working directly with engineers on architecture, tradeoffs, and AI-enabled product capabilities.
• →Rethink the product development lifecycle. Challenge each stage, from scoping and design through review, testing, deployment, and monitoring, and replace manual friction with agentic workflows wherever it makes sense. Build evaluation pipelines, automated PR hygiene, deployment gating, and generation-to-merge metrics that make governed AI fast, not slow.
• →Define quality for AI-powered products. Work with engineering to set the benchmarks and quality gates that tell us whether our AI is working, degrading, or ready to ship, and make results visible and trustworthy across teams.
• →Graduate pilots to production. Take what’s working in engineering experiments and turn it into something the next team can fork and ship in a week. Build reusable libraries, templates, and reference implementations so no one solves the same problem twice.
• →Build toward zero-to-one. Learn how EarnIn works, including how to partner with legal and compliance, so you can lead new product initiatives from idea to launch. Stay close to our community. Use user research and data analytics to identify and prioritize product opportunities, and run features and experiments to refine our products quickly.
• →Lead across functions. Work with a cross-functional team of engineers, designers, researchers, and analysts. Define ambitious OKRs and stretch goals, and monitor the metrics that show product success.
• →Communicate the vision. Articulate the product vision, roadmap, and outcomes to internal stakeholders, including the executive team, and build consensus to get new work done.

• 4+ years of relevant industry experience in product management or engineering.
• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Engineering, Information Systems, or a related field, or equivalent industry experience. 
• Hands-on experience with AI native product development lifecycles (PDLC).
• Proficiency and comfort working across the stack when needed
• Strong analytical skills, using data to inform product decisions and drive metrics improvement
• Deep empathy for user needs
• Exceptional communication skills with executive leadership and key stakeholders
• Comfort in a culture of rapid experimentation, and the ability to build alignment across teams and functions
• Creative problem solving for complex challenges

• Experience in fintech or regulated, security-sensitive environments, including knowledge of regulatory requirements and best practices
• Hands-on work with AI governance: bias evaluation, audit logging, model cards
• Exposure to multi-step reasoning pipelines or human-in-the-loop system design

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